A computational approach towards the microscale mouse brain connectome from the mesoscale

doi:10.3233/JIN-170019

	A computational approach towards the microscale mouse brain connectome from the mesoscale
	Zhang, Tielin1 ; Zeng, Yi1,2,3 ; Xu, Bo1,2,3
发表期刊	JOURNAL OF INTEGRATIVE NEUROSCIENCE
	2017
卷号	16 期号:3 页码:291-306
文章类型	Article
摘要	The wiring diagram of the mouse brain presents an indispensable foundation for the research on basic and applied neurobiology. It is also essential as a structural foundation for computational simulation of the brain. Different scales of the connectome give us different hints and clues to understand the functions of the nervous system and how they process information. However, compared to the macroscale and most recent mesoscale mouse brain connectome studies, there is no complete whole brain microscale connectome available because of the scalability and accuracy of automatic recognition techniques. Different scales of the connectivity data are comprehensive descriptions of the whole brain at different levels of details. Hence connectivity results from a neighborhood scale may help to predict each other. Here we report a computational approach to bring the mesoscale connectome a step forward towards the microscale from the perspective of neuron, synapse and network motifs distribution by the connectivity data at the mesoscale and some facts from the anatomical experiments at the microscale. These attempts make a step forward towards the efforts of microscale mouse brain connectome given the fact that the detailed microscale connectome results are still far to be produced due to the limitation of current nano-scale 3-D reconstruction techniques. The generated microscale mouse brain will play a key role on the understanding of the behavioral and cognitive processes of the mouse brain. In this paper, the conversion method which could get the approximate number of neurons and synapses in microscale is proposed and tested in sub-regions of Hippocampal Formation (HF), and is generalized to the whole brain. As a step forward towards understanding the microscale connectome, we propose a microscale motif prediction model to generate understanding on the microscale structure of different brain region from network motif perspective. Correlation analysis shows that the predicted motif distribution is very relevant to the real anatomical brain data at microscale.
关键词	Microscale Mouse Brain Connectome Brain Connectivity Atlas Motif Distribution Synaptic Degree Distribution Analysis
WOS标题词	Science & Technology ; Life Sciences & Biomedicine
DOI	10.3233/JIN-170019
关键词[WOS]	NETWORK ; CORTEX ; NUMBER ; VOLUME
收录类别	SCI
语种	英语
项目资助者	Chinese Academy of Sciences(XDB02060007) ; Beijing Municipal Commission of Science and Technology(Z161100000216124)
WOS研究方向	Neurosciences & Neurology
WOS类目	Neurosciences
WOS记录号	WOS:000402301000004
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/15122
专题	脑图谱与类脑智能实验室_类脑认知计算
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 2.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Zhang, Tielin,Zeng, Yi,Xu, Bo. A computational approach towards the microscale mouse brain connectome from the mesoscale[J]. JOURNAL OF INTEGRATIVE NEUROSCIENCE,2017,16(3):291-306.
APA	Zhang, Tielin,Zeng, Yi,&Xu, Bo.(2017).A computational approach towards the microscale mouse brain connectome from the mesoscale.JOURNAL OF INTEGRATIVE NEUROSCIENCE,16(3),291-306.
MLA	Zhang, Tielin,et al."A computational approach towards the microscale mouse brain connectome from the mesoscale".JOURNAL OF INTEGRATIVE NEUROSCIENCE 16.3(2017):291-306.

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